Cargando…

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the...

Descripción completa

Detalles Bibliográficos
Autores principales: Palanisamy, Thirumoorthy, Krishnasamy, Karthikeyan N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4591332/
https://www.ncbi.nlm.nih.gov/pubmed/26426701
http://dx.doi.org/10.1371/journal.pone.0138932
_version_ 1782393061288968192
author Palanisamy, Thirumoorthy
Krishnasamy, Karthikeyan N.
author_facet Palanisamy, Thirumoorthy
Krishnasamy, Karthikeyan N.
author_sort Palanisamy, Thirumoorthy
collection PubMed
description Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.
format Online
Article
Text
id pubmed-4591332
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-45913322015-10-09 Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network Palanisamy, Thirumoorthy Krishnasamy, Karthikeyan N. PLoS One Research Article Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead. Public Library of Science 2015-10-01 /pmc/articles/PMC4591332/ /pubmed/26426701 http://dx.doi.org/10.1371/journal.pone.0138932 Text en © 2015 Palanisamy, Krishnasamy http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Palanisamy, Thirumoorthy
Krishnasamy, Karthikeyan N.
Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network
title Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network
title_full Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network
title_fullStr Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network
title_full_unstemmed Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network
title_short Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network
title_sort bayes node energy polynomial distribution to improve routing in wireless sensor network
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4591332/
https://www.ncbi.nlm.nih.gov/pubmed/26426701
http://dx.doi.org/10.1371/journal.pone.0138932
work_keys_str_mv AT palanisamythirumoorthy bayesnodeenergypolynomialdistributiontoimproveroutinginwirelesssensornetwork
AT krishnasamykarthikeyann bayesnodeenergypolynomialdistributiontoimproveroutinginwirelesssensornetwork